Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits

Autor: Min Wang, Michael E. Goddard, Hans D. Daetwyler, Zhiqian Liu, Sunduimijid Bolormaa, Coralie M. Reich, Christy J. Vander Jagt, Amanda J. Chamberlain, Irene van den Berg, Claire P. Prowse-Wilkins, Iona M. MacLeod, Brett A. Mason, Benjamin J. Hayes, Mogens Sandø Lund, Simone Rochfort, Ruidong Xiang
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Male
Multifactorial Inheritance
Genome-wide association study
Breeding
Genome
0302 clinical medicine
Databases
Genetic

2. Zero hunger
Regulation of gene expression
0303 health sciences
Multidisciplinary
biology
Agricultural Sciences
Vertebrate
04 agricultural and veterinary sciences
animal breeding
Biological Sciences
Biological Evolution
Histone
Phenotype
PNAS Plus
Trait
Female
Evolution
Quantitative Trait Loci
Quantitative trait locus
quantitative traits
03 medical and health sciences
biology.animal
Genetic variation
evolution
Animals
Selection
Genetic

Selection (genetic algorithm)
030304 developmental biology
Animal breeding
0402 animal and dairy science
Quantitative traits
Genetic Variation
Heritability
040201 dairy & animal science
Gene regulation
Gene Expression Regulation
Evolutionary biology
cattle
Expression quantitative trait loci
biology.protein
Human genome
Cattle
gene regulation
030217 neurology & neurosurgery
Genome-Wide Association Study
Zdroj: Proceedings of the National Academy of Sciences of the United States of America
Xiang, R, Van Den Berg, I, MacLeod, I M, Hayes, B J, Prowse-Wilkins, C P, Wang, M, Bolormaa, S, Liu, Z, Rochfort, S J, Reich, C M, Mason, B A, Vander Jagt, C J, Daetwyler, H D, Lund, M S, Chamberlain, A J & Goddard, M E 2019, ' Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits ', Proceedings of the National Academy of Sciences of the United States of America, vol. 116, no. 39, pp. 19398-19408 . https://doi.org/10.1073/pnas.1904159116
ISSN: 1091-6490
0027-8424
Popis: Significance The extent to which variants with genome regulatory and evolutionary roles affect mammalian phenotypes is unclear. We systemically analyzed large datasets covering genomics, transcriptomics, epigenomics, metabolomics, and 34 phenotypes in over 44,000 cattle. This allowed us to provide a framework to rank over 17.7 million sequence variants based on their contribution to gene regulation, evolution, and variation in 34 complex traits. Validated in independent datasets with over 7,500 cattle, our sequence-variant ranking showed consistent performances in genomic prediction of phenotypes. Our study provides methods and an analytical framework to quantify the functional importance of sequence variants. By providing public data of biological priors on genomic markers, our work can make the global selection of animals efficient and accurate.
Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits in a different mammalian model is needed. Sequence variants associated with gene expression (expression quantitative trait loci [eQTLs]) and concentration of metabolites (metabolic quantitative trait loci [mQTLs]) and under histone-modification marks in several tissues were discovered from multiomics data of over 400 cattle. Variants under selection and evolutionary constraint were identified using genome databases of multiple species. These analyses defined 30 sets of variants, and for each set, we estimated the genetic variance the set explained across 34 complex traits in 11,923 bulls and 32,347 cows with 17,669,372 imputed variants. The per-variant trait heritability of these sets across traits was highly consistent (r > 0.94) between bulls and cows. Based on the per-variant heritability, conserved sites across 100 vertebrate species and mQTLs ranked the highest, followed by eQTLs, young variants, those under histone-modification marks, and selection signatures. From these results, we defined a Functional-And-Evolutionary Trait Heritability (FAETH) score indicating the functionality and predicted heritability of each variant. In additional 7,551 cattle, the high FAETH-ranking variants had significantly increased genetic variances and genomic prediction accuracies in 3 production traits compared to the low FAETH-ranking variants. The FAETH framework combines the information of gene regulation, evolution, and trait heritability to rank variants, and the publicly available FAETH data provide a set of biological priors for cattle genomic selection worldwide.
Databáze: OpenAIRE